Box-and-whisker plots or simply boxplots are powerful graphical representations that give an overview of a data set. In this work five different examples illustrate the applications of boxplots in food chemistry. The examples involve relative sweetness of sugars and sugar alcohols with respect to sucrose, the potassium content of fruits and vegetables, amino acid content of egg white and yolk, chemical composition of freshwater and saltwater fish, and change in fatty acid composition of soybean oil through traditional cultivation or genetic engineering techniques. Readers are guided to identify through boxplots key features present in some foods associated with inorganic elements and molecules. It is certainly an interdisciplinary way of studying concepts of statistics, nutrition, and chemistry.

No abstract

Teachers select multiple representations and adopt multiple visualization approaches in supporting their students to make meaning of chemical phenomena. Representational competence underpins students’ construction of their mental models of concepts thus it is important that teachers consider this while developing instructional resources. In tertiary chemistry, teachers typically use PowerPoint slides to guide lectures. This instructional resource is transferred between different teachers each semester and, while the sequence of topics are likely to be discussed and agreed upon, the content of the slides can evolve organically in this shared resource over time. The aim of this study was to analyse a teacher-generated resource in the form of a consensus set of course slides to characterise the combination and diversity in representations that students had encountered. This study was set in a unique context since the semester's lecture slides represented a distillation of consensus representations used by multiple chemistry lecturers for at least a decade. The representations included: those created by the lecturers; textbook images (from several texts); photographs and images sourced from the internet. Individual representations in each PowerPoint slide were coded in terms of the level of representation, mode and potential function in supporting deeper understanding of chemistry concepts. Three representational organizing frameworks (functional taxonomy of multiple representations, modes of representation and the chemistry triplet levels of thinking) were integrated to categorise the representations. This qualitative data was subjected to hierarchical cluster analysis and several relationships between the categories and topics taught were identified. Additional qualitative data in the form of student reflections on the perceived utility of specific representations were collected at the end of the semester. The findings from this study inform the design and choice of instructional resources for general chemistry particularly in combining representations to support deeper learning of concepts. A broader goal and application of the findings of this study is to identify opportunities for translation of representations into alternative modalities to widen access and participation in learning chemistry for all students. An example of a strategy for translating representations into tactile modes for teaching the topic of phase change is shared.

Graphics play an important role in data analysis. Boxplots are powerful graphical representation of data that gives an overview and a numerical summary of a data set. In this paper boxplots are used to analyze the periodic trends of main elements. The properties considered are atomic radius, first ionization energy, electron affinity and electronegativity. Boxplots are constructed and metals, nonmetals and metalloids are compared. The results are presented in a manner not explored in chemistry textbooks, pointing out key chemical features visualized through median, quartiles, possible outliers and shape of the distribution. These pictorial representations can show similarities, differences, trends and irregularities among elements, groups and periods, which help better understand their characteristics.

Artemisinin and 18 derivatives with antimalarial activity against W-2 strains of Plasmodium falciparum were studied through quantum chemistry and multivariate analysis. The geometry optimization of the structures was realized with the Hartree-Fock (HF) theory and 3-21G basis set. Maps of molecular electrostatic potential (MEP) and molecular docking were used to investigate the interaction between the ligands and the receptor (heme). Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were employed to select the most important descriptors related to activity. A predictive model was generated by the Partial Least Square (PLS) method through 15 molecules and 4 used as an external validation set, which were selected in the training set, the validation parameters of which are Q2 = 0.85 and R2 = 0.86. The model included as molecular parameters, the radial distribution function, RDF060e, the hydration energy, HE, and the distance between the O1 atom from the ligand and the iron atom from heme, d(Fe-O1). Thus, the synthesis of new derivatives may follow the results of the MEP maps and the PLS analysis